3 research outputs found

    Study and analysis of motion artifacts for ambulatory electroencephalography

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    Motion artifacts contribute complexity in acquiring clean electroencephalography (EEG) data. It is one of the major challenges for ambulatory EEG. The performance of mobile health monitoring, neurological disorders diagnosis and surgeries can be significantly improved by reducing the motion artifacts. Although different papers have proposed various novel approaches for removing motion artifacts, the datasets used to validate those algorithms are questionable. In this paper, a unique EEG dataset was presented where ten different activities were performed. No such previous EEG recordings using EMOTIV EEG headset are available in research history that explicitly mentioned and considered a number of daily activities that induced motion artifacts in EEG recordings. Quantitative study shows that in comparison to correlation coefficient, the coherence analysis depicted a better similarity measure between motion artifacts and motion sensor data. Motion artifacts were characterized with very low frequency which overlapped with the Delta rhythm of the EEG. Also, a general wavelet transform based approach was presented to remove motion artifacts. Further experiment and analysis with more similarity metrics and longer recording duration for each activity is required to finalize the characteristics of motion artifacts and henceforth reliably identify and subsequently remove the motion artifacts in the contaminated EEG recordings

    Water Body Mapping and Monitoring using Landsat Time Series Satellite Images

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    Bangladesh is believed to be extremely vulnerable to climate change, which may result in abnormal spatio-temporal pattern in rainfall and increased variability of temperature across the region. Consequently, the frequency and intensity of various natural hazards are expected to increase, which may affect the availability of fresh water on the surface as well as underground. That’s why mapping of water body and its continuous monitoring is important (Regional Water Report 37, FAO 2011).This study aims at identifying water body in the coastal belt of Bangladesh using Landsat 5 TM time-series satellite images for the year 2000, 2005 and 2010. Satellite derived indices e.g. WRI, NDVI, NDWI, MNDWI, AWEI, NDMI are computed from Landsat data of 2000, which were compared with the base map for selecting the best index for water body identification. The result shows that NDWI is more robust in extracting water bodies compared to other indices. Furthermore, unsupervised and supervised image classification techniques have been applied on all three years data. Both the index images as well as the classified images are reclassified to produce binary images showing water and non-water area. Average accuracy of the classification is 88%. Result shows that there is remarkable increase in water area after 2005. The reason might be attributed to the fact that the study area has suffered from several natural calamities during the study period.Keywords: Water Security, Landsat Satellite Image, Remote Sensing Indices, Mapping and Monitorin

    Prediction of land cover change based on CA-ANN model to assess its local impacts on Bagerhat, southwestern coastal Bangladesh

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    This study aims to assess land use dynamics of Southwestern coastal Bangladesh using multi-temporal Landsat images. Future trend was done by CA-ANN model. Hybrid image classification method and estimation of land surface temperature along with field survey were accomplished. This study revealed that vegetation decreased significantly (11.75%) and converted mostly into wetlands whereas built-up area slightly increased (1.44%) during 2000 to 2016. According to FGD (focused Group Discussion), a major occupational transformation (from agriculture to shrimp cultivation) and internal migration towards nearby Cities are prominent here. Besides, maximum land surface temperature increased by 12.5ËšC during this period as a result of land use change. Simulated land use model of 2024 revealed that 2.49% of settlement would diminish especially from southern region if any natural calamity occurs. Finally, a comprehensive land use management plan has been suggested in this study to establish a balanced and diversified use of coastal land
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